Contemporary solutions for assessing the icing conditions of various surfaces and related elements differ considerably depending on the implementation and related use scenario.
Atmospheric icing takes place when water droplets in the atmosphere freeze on a contacted object. For example, in connection with aircrafts the ice may increase the risk of stalling of the airfoil. Thereby, the ice built-up should be detected as early and reliably as possible. For instance, an electromechanical probe with an oscillating (vibrating) sensing element may be provided on the nose of the aircraft, whereupon the ice accreted thereon causes changes in the oscillation frequency depending on the thickness of the ice layer. The oscillation frequency is monitored for estimating the amount of ice.
As another use scenario, the wind turbines of wind farms may be heavily affected by ice on the rotor blades. The blades may crack and the production efficiency may drastically decrease. The overall wear of the turbine may also increase due to mass and aerodynamic imbalances and additional friction all caused by the ice. Introduction of the aforesaid oscillating probe into the nacelle of a wind turbine has been suggested, so has been the use of various capacitance-, impedance-, and inductance-based detectors requiring the addition of specific sensors on the rotor blades. Further, different optical sensors monitoring the ice accumulated on a sensor surface based on e.g. changes on light reflection from the surface have been set forth.
However, e.g. the oscillation probe may not suit all use scenarios and may turn out too slow as to the achieved detection response. It is relatively complex by nature and requires integration with the turbine nacelle. The capacitance/impedance/inductance-based sensors may, on the other hand, work unreliably after the first detection as the ice removal from the sensor by heating, for example, may easily at least partially fail, whereupon the subsequent detections may be inaccurate. Similar flaws have been recognized with many optical sensing solutions.
In summary, many known arrangements to detect icing still suffer from reliability problems at least in certain type of operational conditions. Yet, their detection areas are limited as they represent only a single or few points in space, i.e. the sensor surface locations. In any case, the arrangements are merely capable of detecting already-formed ice, which may be too late depending on the application.
To broadly just estimate the icing potential in the atmosphere a number of solutions have been disclosed most of which utilizing a plurality of more or less directly measurable prognostic weather parameters such as temperature and humidity combined via a deduction logic to predict icing. Even these solutions typically bear many weaknesses comparable to the ones already contemplated above.